Microbial infections are complex, dynamic processes that evolve constantly within the host. In many instances, virulence gene expression is modulated in response to the changing environment encountered at the site of infection. Mekalanos, J. Bacteriol. 174:1-7 (1992); Mahan et al. Science 259:686-688 (1993). It is unlikely that all regulated virulence determinants of a pathogen can be identified in vitro because it is technically impossible to determine and mimic all of the complex and changing environmental stimuli that occur at the site of an infection. Pioneering technologies such as in vivo expression technology (IVET), signature-tagged mutagenesis (STM) and differential fluorescence induction (DFI) were designed to identify genes specifically expressed in vivo, and fill the gaps in our understanding of microbial pathogenesis. Handfield & Levesque, FEMS Microbiol. Rev. 23:69-91 (1999); Heithoff et al., Trends Microbiol. 5:509-513 (1997); Chiang et al., Ann. Rev. Microbiol. 53:129-154 (1999); Hautefort & Hinton, Phil. Trans. R. Soc. London Ser. B, 255:601-611 (2000). All of these methods depend on a reasonable assumption: namely, that genes which are specifically induced during in vivo growth are likely to be important to the pathogenic process.
Although remarkably powerful, all of these technologies have certain limitations. Their major drawback is that they depend on the use of animal models of infection; animal models are not available for many pathogens and, in those cases where an animal model is available, it might not closely approximate the human condition. Consequently, a number of examples exist in the literature of erroneous conclusions being drawn by extrapolation of results from animal models to human infections. Smith, Trends Microbiol. 6:239-243 (1998). Further, many of these schemes are not readily applicable to genetically “undomesticated” microbes, that is microbes for which there is no well established or reliable means for genetic manipulation. Additionally, IVET, STM, and related technologies are technically difficult, and therefore restrict analysis to a single representative strain of the microbe and to only one or several time points in the infection process.
An example of a microbe that is not easily characterized by IVET, STM, and related technologies is Actinobacillus actinomycetemcomitans (Aa), an etiologic agent of periodontal diseases. Aa has emerged as one of the best examples of a bacterium demonstrating a direct correlation with disease manifestation in the oral cavity. Act is known to be the etiologic agent for localized juvenile periodontitis (LJP). See, Slots & Ting, Periodontol. 2000, 20:82-121 (1999). Despite the fact that some Aa virulence factors have been identified, other important contributors to the infectious process have yet to be identified.